World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
36
Citations
4472
World Ranking
9175
National Ranking
116

Ole Martin Bollandsås publication distribution in Environmental Sciences in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Environmental Sciences in 2026. The highlighted bar marks where Ole Martin Bollandsås sits on this spectrum.

41–50 publications: 21 scientists 51–60 publications: 62 scientists 61–70 publications: 133 scientists 71–80 publications: 257 scientists 81–90 publications: 361 scientists 91–100 publications: 440 scientists 101–110 publications: 492 scientists 111–120 publications: 541 scientists 121–130 publications: 617 scientists 131–140 publications: 544 scientists 141–150 publications: 541 scientists 151–160 publications: 539 scientists 161–170 publications: 444 scientists 171–180 publications: 444 scientists 181–190 publications: 400 scientists 191–200 publications: 377 scientists 201–210 publications: 318 scientists 211–220 publications: 283 scientists 221–230 publications: 263 scientists 231–240 publications: 220 scientists 241–250 publications: 217 scientists 251–260 publications: 180 scientists 261–270 publications: 181 scientists 271–280 publications: 155 scientists 281–290 publications: 130 scientists 291–300 publications: 127 scientists 301–310 publications: 130 scientists 311–320 publications: 85 scientists 321–330 publications: 106 scientists 331–340 publications: 80 scientists 341–350 publications: 83 scientists 351–360 publications: 75 scientists 361–370 publications: 69 scientists 371–380 publications: 52 scientists 381–390 publications: 54 scientists 391–400 publications: 56 scientists 401–410 publications: 44 scientists 411–420 publications: 40 scientists 421–430 publications: 36 scientists 431–440 publications: 25 scientists 441–450 publications: 25 scientists 451–460 publications: 32 scientists 461–470 publications: 29 scientists 471–480 publications: 21 scientists 481–490 publications: 26 scientists 491–500 publications: 25 scientists 501–510 publications: 17 scientists 511–520 publications: 18 scientists 521–530 publications: 15 scientists 531–540 publications: 22 scientists 541–550 publications: 12 scientists 551–560 publications: 15 scientists 561–570 publications: 11 scientists 571–580 publications: 19 scientists 581–590 publications: 9 scientists 591–600 publications: 9 scientists 601–610 publications: 7 scientists 611–620 publications: 11 scientists 621–630 publications: 5 scientists 631–640 publications: 5 scientists 641–650 publications: 6 scientists 651–660 publications: 3 scientists 661–670 publications: 3 scientists 671–680 publications: 4 scientists 681–686 publications: 3 scientists 687+ publications: 100 scientists
41 publications 687+

This scientist: 79 publications — 5th percentile

5% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 687 publications or more.

Ole Martin Bollandsås D-index placement in Environmental Sciences in 2026

The chart shows the D-index (discipline H-index) distribution of Environmental Sciences scientists ranked by Research.com in 2026. The highlighted bar marks where Ole Martin Bollandsås sits on this spectrum.

30 D-Index: 12 scientists 31 D-Index: 26 scientists 32 D-Index: 51 scientists 33 D-Index: 88 scientists 34 D-Index: 123 scientists 35 D-Index: 163 scientists 36 D-Index: 206 scientists 37 D-Index: 267 scientists 38 D-Index: 265 scientists 39 D-Index: 275 scientists 40 D-Index: 321 scientists 41 D-Index: 343 scientists 42 D-Index: 305 scientists 43 D-Index: 336 scientists 44 D-Index: 330 scientists 45 D-Index: 348 scientists 46 D-Index: 291 scientists 47 D-Index: 275 scientists 48 D-Index: 272 scientists 49 D-Index: 273 scientists 50 D-Index: 263 scientists 51 D-Index: 232 scientists 52 D-Index: 266 scientists 53 D-Index: 217 scientists 54 D-Index: 199 scientists 55 D-Index: 177 scientists 56 D-Index: 202 scientists 57 D-Index: 204 scientists 58 D-Index: 166 scientists 59 D-Index: 177 scientists 60 D-Index: 166 scientists 61 D-Index: 152 scientists 62 D-Index: 143 scientists 63 D-Index: 150 scientists 64 D-Index: 124 scientists 65 D-Index: 119 scientists 66 D-Index: 120 scientists 67 D-Index: 118 scientists 68 D-Index: 82 scientists 69 D-Index: 98 scientists 70 D-Index: 94 scientists 71 D-Index: 105 scientists 72 D-Index: 74 scientists 73 D-Index: 84 scientists 74 D-Index: 70 scientists 75 D-Index: 67 scientists 76 D-Index: 78 scientists 77 D-Index: 60 scientists 78 D-Index: 59 scientists 79 D-Index: 52 scientists 80 D-Index: 47 scientists 81 D-Index: 38 scientists 82 D-Index: 48 scientists 83 D-Index: 42 scientists 84 D-Index: 42 scientists 85 D-Index: 43 scientists 86 D-Index: 29 scientists 87 D-Index: 37 scientists 88 D-Index: 29 scientists 89 D-Index: 30 scientists 90 D-Index: 34 scientists 91 D-Index: 20 scientists 92 D-Index: 22 scientists 93 D-Index: 17 scientists 94 D-Index: 19 scientists 95 D-Index: 24 scientists 96 D-Index: 21 scientists 97 D-Index: 20 scientists 98 D-Index: 24 scientists 99 D-Index: 17 scientists 100 D-Index: 17 scientists 101 D-Index: 21 scientists 102 D-Index: 25 scientists 103 D-Index: 18 scientists 104 D-Index: 26 scientists 105 D-Index: 19 scientists 106 D-Index: 15 scientists 107 D-Index: 10 scientists 108 D-Index: 13 scientists 109 D-Index: 15 scientists 110 D-Index: 12 scientists 111 D-Index: 8 scientists 112 D-Index: 7 scientists 113 D-Index: 9 scientists 114 D-Index: 6 scientists 115 D-Index: 12 scientists 116 D-Index: 7 scientists 117 D-Index: 8 scientists 118 D-Index: 3 scientists 119 D-Index: 5 scientists 120 D-Index: 7 scientists 121 D-Index: 2 scientists 122 D-Index: 4 scientists 123 D-Index: 8 scientists 124 D-Index: 7 scientists 125+ D-Index: 99 scientists
30 D-Index 125+

This scientist: 36 D-Index — 7th percentile

7% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 125 D-Index or more.

Overview

Ole Martin Bollandsås is affiliated with the Norwegian University of Life Sciences in Norway. Their research focuses on the interface between environmental science and earth and planetary sciences, with significant contributions to subfields such as nature and landscape conservation, environmental engineering, atmospheric science, global and planetary change, and ecology.

The scientist's work chiefly explores topics related to remote sensing and LiDAR applications, forest ecology and management, tree-ring climate responses, remote sensing in agriculture, forest ecology and biodiversity studies, cryospheric studies and observations, and forest management and policy.

Ole Martin Bollandsås has published extensively, including papers such as:

  • Relationships between single-tree mountain birch summertime albedo and vegetation properties (2021) in Agricultural and Forest Meteorology
  • Land cover classification of treeline ecotones along a 1100 km latitudinal transect using spectral- and three-dimensional information from UAV-based aerial imagery (2022) in Remote Sensing in Ecology and Conservation
  • Soil carbon stocks in forest-tundra ecotones along a 500 km latitudinal gradient in northern Norway (2022) in Scientific Reports
  • The relative role of climate and herbivory in driving treeline dynamics along a latitudinal gradient (2020) in Journal of Vegetation Science
  • Reuse of field data in ALS-assisted forest inventory (2020) in Silva Fennica

The frequent coauthors of Bollandsås include:

  • Erik Næsset (20 joint publications)
  • Terje Gobakken (19 joint publications)
  • Hans Ole Ørka (13 joint publications)
  • Lennart Noordermeer (7 joint publications)
  • Ida Marielle Mienna (5 joint publications)

Publication venues where Bollandsås has frequently contributed include:

  • Silva Fennica (4 publications)
  • SSRN Electronic Journal (4 publications)
  • Scandinavian Journal of Forest Research (3 publications)
  • Forestry An International Journal of Forest Research (3 publications)
  • Remote Sensing (3 publications)

Best Publications

  • Classifying species of individual trees by intensity and structure features derived from airborne laser scanner data

    Hans Ole Ørka;Erik Næsset;Ole Martin Bollandsås

  • Single Tree Segmentation Using Airborne Laser Scanner Data in a Structurally Heterogeneous Spruce Forest

    Svein Solberg;Erik Naesset;Ole Martin Bollandsas

  • Allometric models for prediction of above- and belowground biomass of trees in the miombo woodlands of Tanzania

    Wilson Ancelm Mugasha;Tron Eid;Ole Martin Bollandsås;Rogers Ernest Malimbwi

  • Comparing regression methods in estimation of biophysical properties of forest stands from two different inventories using laser scanner data

    Erik Næsset;Ole Martin Bollandsås;Terje Gobakken

  • Model-assisted estimation of change in forest biomass over an 11year period in a sample survey supported by airborne LiDAR: A case study with post-stratification to provide ``activity data''

    Erik Næsset;Ole Martin Bollandsås;Terje Gobakken;Timothy G. Gregoire

  • Estimating biomass in Hedmark County, Norway using national forest inventory field plots and airborne laser scanning

    Terje Gobakken;Erik Næsset;Ross Nelson;Ole Martin Bollandsås

  • Comparing biophysical forest characteristics estimated from photogrammetric matching of aerial images and airborne laser scanning data

    Terje Gobakken;Ole Martin Bollandsås;Erik Næsset

  • Mapping and estimating forest area and aboveground biomass in miombo woodlands in Tanzania using data from airborne laser scanning, TanDEM-X, RapidEye, and global forest maps: A comparison of estimated precision

    Erik Næsset;Hans Ole Ørka;Svein Solberg;Ole Martin Bollandsås

  • Comparison of precision of biomass estimates in regional field sample surveys and airborne LiDAR-assisted surveys in Hedmark County, Norway

    Erik Naesset;Terje Gobakken;Ole Martin Bollandsas;Timothy G. Gregoire

  • Different plot selection strategies for field training data in ALS-assisted forest inventory

    M. Maltamo;O. M. Bollandsås;E. Næsset;T. Gobakken

  • Predicting the growth of stands of trees of mixed species and size: A matrix model for Norway

    Ole Martin Bollandsås;Joseph Buongiorno;Terje Gobakken

  • Effects of different sensors and leaf-on and leaf-off canopy conditions on echo distributions and individual tree properties derived from airborne laser scanning

    Hans Ole Ørka;Erik Næsset;Ole Martin Bollandsås

  • Mapping and estimating the total living biomass and carbon in low-biomass woodlands using Landsat 8 CDR data

    Belachew Gizachew;Svein Solberg;Erik Næsset;Terje Gobakken

  • Indirect and direct estimation of forest biomass change using forest inventory and airborne laser scanning data

    Ronald E. McRoberts;Erik Næsset;Terje Gobakken;Ole Martin Bollandsås

  • Effects of field plot size on prediction accuracy of aboveground biomass in airborne laser scanning-assisted inventories in tropical rain forests of Tanzania

    Ernest William Mauya;Endre Hofstad Hansen;Terje Gobakken;Ole Martin Bollandsås

  • Modeling Aboveground Biomass in Dense Tropical Submontane Rainforest Using Airborne Laser Scanner Data

    Endre Hofstad Hansen;Terje Gobakken;Ole Martin Bollandsås;Eliakimu Zahabu

  • Detection of biomass change in a Norwegian mountain forest area using small footprint airborne laser scanner data

    Ole Martin Bollandsås;Timothy G. Gregoire;Erik Næsset;Bernt-Håvard Øyen

  • Forest biomass change estimated from height change in interferometric SAR height models.

    Svein Solberg;Erik Næsset;Terje Gobakken;Ole Martin Bollandsås

  • The effects of field plot size on model-assisted estimation of aboveground biomass change using multitemporal interferometric SAR and airborne laser scanning data

    Erik Næsset;Ole Martin Bollandsås;Terje Gobakken;Svein Solberg

  • Relationships between diameter and height of trees in natural tropical forest in Tanzania

    Wilson A Mugasha;Ole M Bollandsås;Tron Eid

  • Large-scale estimation of change in aboveground biomass in miombo woodlands using airborne laser scanning and national forest inventory data

    Liviu Theodor Ene;Erik Næsset;Terje Gobakken;Ernest William Mauya

  • Different plot selection strategies for field training data in ALS-assisted forest

    M. Maltamo;O. M. Bollandsås;E. Næsset;T. Gobakken

Frequent Co-Authors

Erik Næsset
Erik Næsset Norwegian University of Life Sciences
Terje Gobakken
Terje Gobakken Norwegian University of Life Sciences
Matti Maltamo
Matti Maltamo University of Eastern Finland
Svein Solberg
Svein Solberg Norwegian Institute of Bioeconomy Research
Timothy G. Gregoire
Timothy G. Gregoire Yale University
Rasmus Astrup
Rasmus Astrup Norwegian Institute of Bioeconomy Research
Ronald E. McRoberts
Ronald E. McRoberts University of Minnesota
Göran Ståhl
Göran Ståhl Swedish University of Agricultural Sciences
Joseph Buongiorno
Joseph Buongiorno University of Wisconsin–Madison
Ross Nelson
Ross Nelson Goddard Space Flight Center

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